Feedback in hearing aid systems is a well-known problem that can occur when there is a feedback path from the output signal of the hearing aid system to the input signal of the hearing aid system. This usually occurs when a user of the hearing aid system is moving his/her jaws (i.e. while eating), wearing a hat, using a telephone, standing close to walls, etc. The feedback usually occurs in mid and high frequency regions which are important for allowing the hearing aid user to understand speech. Accordingly, feedback is not only annoying but impairs speech comprehension for the hearing aid user. Feedback can also be due to other causes such as magnetic, vibrational or electrical.
Many different feedback reduction approaches have been developed to cancel feedback when it occurs in the hearing aid system. Some of these approaches comprise estimating a feedback path transfer function and altering the feedback path transfer function at critical frequencies (i.e. feedback prone frequencies) to remove feedback. The feedback path transfer function can be estimated via auto-correlation of the input signal and/or cross-correlation of the input signal and the output signal. This approach may also be adaptive by incorporating a variation of the Least Mean Square algorithm for adaptive estimation of the feedback transfer function. Consequently, this approach requires rather high levels of computational power, and due to the limited computational power of available digital hearing aid systems, the effectiveness of this approach is restricted particularly in dealing with the multiple feedback paths that usually occur in daily life.
Another approach for reducing feedback in hearing aid systems is to use a notch filter. A single notch filter may effectively reduce feedback when the overall loop gain in a single narrow frequency band reaches values larger than unity and the phase of the feedback signal is 0° or a multiple of 360° (i.e. the Nyquist criterion). If the loop gain begins to exceed unity and the corresponding phase satisfies the Nyquist criterion in several frequency bands that lie far apart, then several notch filters may be used. However, the notch filters have to be tuned to the correct frequencies at which the feedback occurs which implies that the frequencies and frequency bands where feedback occurs must be detected. Detection of a single frequency feedback signal in noise may involve signal processing techniques such as correlation and parametric modeling methods, followed by peak picking, zero crossing counters, etc., as is well known to those skilled in the art. Accordingly, this method of feedback cancellation also requires high levels of computational power that can exceed the computational power available in hearing aid systems.
Another approach for reducing feedback in the hearing aid system is anti-phase feedback canceling. This involves adaptively detecting changes in the feedback path, and once feedback is detected, generating an anti-phase feedback signal to cancel the feedback. If the hearing aid system is linear, the feedback path changes slowly, and only a small number of feedback paths exist (such as one or two), anti-phase feedback canceling works well. However, the feedback path can change dramatically and very rapidly in real-life situations. Furthermore, most of the advanced digital hearing aid systems are not linear and incorporate some type of input or output referred compression. Accordingly, the gain of the hearing aid system changes constantly as the input or output signal levels change. The feedback signal level is therefore not constant, as it is for a linear hearing aid system. In addition, multiple feedback paths usually occur as well as temporary feedback path changes. All of these factors result in high computational demand which can limit the application of the anti-phase feedback canceling technique in hearing aid systems, particularly when dealing with multi-feedback path situations.
Another approach for reducing feedback in the hearing aid system, while addressing the limited computational power in the hearing aid system, is to use a non-adaptive feedback manager. The most basic feedback manager is a static feedback manager that permanently reduces the maximum loop gain to prevent the occurrence of feedback in the hearing aid system. Although this approach can be effective, reducing the maximum system gain limits the user's access to higher gain, which may be required on occasion depending on the individual's hearing loss. Since feedback often occurs in the higher frequency range, which is also the frequency range that contains the consonant sounds of speech, reducing the gain in this frequency range can have detrimental effects on speech discrimination. In addition, the static feedback manager cannot dynamically compensate for temporary feedback caused when a hand or a telephone is placed close to or on the hearing aid system, or if the user distorts the ear canal with jaw movements.
Another characteristic of these prior art feedback reduction methods is that they typically require a few hundred milliseconds (i.e. 200 ms) to detect the occurrence of feedback and then another few hundred milliseconds (i.e. 200 ms) to eliminate the feedback. Accordingly, the user of the hearing aid system will hear a short, but very loud, burst of feedback before the feedback is suppressed. This is detrimental since such a feedback signal can be uncomfortable and annoying for the hearing aid user.